Reducing communication in federated learning via efficient client sampling-Reference-Cited by-同舟云学术

Reducing communication in federated learning via efficient client sampling

Published:2024-04 Issue: Volume:148 Page:110122
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Ribero Mónica,Vikalo Haris^ORCID

Funder

National Institute of Standards and Technology

National Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference46 articles.

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2. Federating recommendations using differentially private prototypes;Ribero;Pattern Recognit.,2022

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4. Bolt-on differential privacy for scalable stochastic gradient descent-based analytics;Wu,2017

5. A general approach to adding differential privacy to iterative training procedures;McMahan,2018

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